Recent upgrades to the Super-Kamiokande neutrino observatory will allow it to trace the history of exploding stars. An upgraded Super-Kamiokande will be able to detect these particles with greatly improved efficiency.
Category: particle physics – Page 567
Neutrinos seen in the clustering of galaxies
In early times, the universe was an energetic mix of strongly interacting particles. The first particles to break free from this dense soup were neutrinos, the lightest and most weakly interacting particles of the Standard Model of particle physics. These neutrinos are still around us today, but are very hard to detect directly because they are so weakly interacting. An international team of cosmologists, including Daniel Baumann and Benjamin Wallisch from the University of Amsterdam, have now succeeded in measuring the influence of this ‘cosmic neutrino background’ on the way galaxies have become clustered during the evolution of the universe. The research was published in Nature Physics this week.
Laser ‘drill’ sets a new world record in laser-driven electron acceleration
Combining a first laser pulse to heat up and “drill” through a plasma, and another to accelerate electrons to incredibly high energies in just tens of centimeters, scientists have nearly doubled the previous record for laser-driven particle acceleration.
The laser-plasma experiments, conducted at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab), are pushing toward more compact and affordable types of particle acceleration to power exotic, high-energy machines—like X-ray free-electron lasers and particle colliders—that could enable researchers to see more clearly at the scale of molecules, atoms, and even subatomic particles.
The new record of propelling electrons to 7.8 billion electron volts (7.8 GeV) at the Berkeley Lab Laser Accelerator (BELLA) Center surpasses a 4.25 GeV result at BELLA announced in 2014. The latest research is detailed in the Feb. 25 edition of the journal Physical Review Letters. The record result was achieved during the summer of 2018.
A quantum magnet with a topological twist
Taking their name from an intricate Japanese basket pattern, kagome magnets are thought to have electronic properties that could be valuable for future quantum devices and applications. Theories predict that some electrons in these materials have exotic, so-called topological behaviors and others behave somewhat like graphene, another material prized for its potential for new types of electronics.
Now, an international team led by researchers at Princeton University has observed that some of the electrons in these magnets behave collectively, like an almost infinitely massive electron that is strangely magnetic, rather than like individual particles. The study was published in the journal Nature Physics this week.
The team also showed that placing the kagome magnet in a high magnetic field causes the direction of magnetism to reverse. This “negative magnetism” is akin to having a compass that points south instead of north, or a refrigerator magnet that suddenly refuses to stick.
Physicists get thousands of semiconductor nuclei to do ‘quantum dances’ in unison
A team of Cambridge researchers have found a way to control the sea of nuclei in semiconductor quantum dots so they can operate as a quantum memory device.
Quantum dots are crystals made up of thousands of atoms, and each of these atoms interacts magnetically with the trapped electron. If left alone to its own devices, this interaction of the electron with the nuclear spins, limits the usefulness of the electron as a quantum bit—a qubit.
Led by Professor Mete Atatüre, a Fellow at St John’s College, University of Cambridge, the research group, located at the Cavendish Laboratory, exploit the laws of quantum physics and optics to investigate computing, sensing or communication applications.
Physicists Have Finally Solved a Fundamental Mystery Concerning The Insides of Atoms
Something about atoms has never added up. Fundamental particles called quarks get kind of sluggish once they’re caught up in crowds of protons and neutrons – and quite frankly, they shouldn’t.
For decades, physicists have hunted for clues on the quark’s tendency to slow down in larger atoms, but have come up empty-handed. But now, a closer look at old data has finally revealed a clue to explain this strange phenomenon.
A massive team of physicists known as the CLAS Collaboration (after the CEBAF Large Acceptance Spectrometer) recently ran through data gathered from previous experiments at the Jefferson Lab’s Continuous Electron Beam Accelerator Facility.
Breakthrough in the search for graphene-based electronics
For 15 years, scientists have tried to exploit the “miracle material” graphene to produce nanoscale electronics. On paper, graphene should be great for just that: it is ultra-thin—only one atom thick and therefore two-dimensional, it is excellent for conducting electrical current, and holds great promise for future forms of electronics that are faster and more energy efficient. In addition, graphene consists of carbon atoms – of which we have an unlimited supply.
In theory, graphene can be altered to perform many different tasks within e.g. electronics, photonics or sensors simply by cutting tiny patterns in it, as this fundamentally alters its quantum properties. One “simple” task, which has turned out to be surprisingly difficult, is to induce a band gap—which is crucial for making transistors and optoelectronic devices. However, since graphene is only an atom thick all of the atoms are important and even tiny irregularities in the pattern can destroy its properties.
“Graphene is a fantastic material, which I think will play a crucial role in making new nanoscale electronics. The problem is that it is extremely difficult to engineer the electrical properties,” says Peter Bøggild, professor atDTU Physics.
Artificial intelligence alone won’t solve the complexity of Earth sciences
One way to crack this problem, according to the authors of a Perspective in this issue, is through a hybrid approach. The latest techniques in deep learning should be accompanied by a hand-in-glove pursuit of conventional physical modelling to help to overcome otherwise intractable problems such as simulating the particle-formation processes that govern cloud convection. The hybrid approach makes the most of well-understood physical principles such as fluid dynamics, incorporating deep learning where physical processes cannot yet be adequately resolved.
Studies of complex climate and ocean systems could gain from a hybrid between artificial intelligence and physical modelling.